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- W2404892103 abstract "Smooth entropy of X is defined as possibly biggest entropy of a distribution Y close to X. It has found many applications including privacy amplification, information reconciliation, quantum information theory and even constructing random number generators. However the basic question about the optimal shape for the distribution Y has not been answered yet. In this paper we solve this problem for Renyi entropies in non-quantum settings, giving a formal treatment to an approach suggested at TCC'05 and ASIACRYPT'05. The main difference is that we use a threshold cut instead of a quantile cut to rearrange probability masses of X. As an example of application, we derive tight lower bounds on the number of bits extractable from Shannon memoryless sources." @default.
- W2404892103 created "2016-06-24" @default.
- W2404892103 creator A5011993100 @default.
- W2404892103 date "2016-01-01" @default.
- W2404892103 modified "2023-09-25" @default.
- W2404892103 title "How to Smooth Entropy?" @default.
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- W2404892103 doi "https://doi.org/10.1007/978-3-662-49192-8_32" @default.
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